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torch export to onnx extern data size configurable #1481

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This PR adds dyn_dim_min_sizes and dyn_dim_max_sizes to the command line options of tools/torch_export_to_onnx.py . In default, extern data with time dimension size in range [2,25] would be generated for export, which might be too short for the cases where raw wave input is used. Thus these two options can be used to specify the min/max sizes for dim tags with dynamic sizes.

@Judyxujj Judyxujj requested review from albertz and a team as code owners December 22, 2023 15:00
@@ -182,6 +182,13 @@ def main():
parser.add_argument("out_onnx_filename", type=str, help="Filename of the final ONNX model.")
parser.add_argument("--verbosity", default=4, type=int, help="5 for all seqs (default: 4)")
parser.add_argument("--device", type=str, default="cpu", help="'cpu' (default) or 'gpu'.")
parser.add_argument(
"--dyn_dim_min_sizes", type=dict, default=None, help="Specify min sizes for dim tags with dynamic sizes"
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Did you test this? What exactly did you pass as argument? I wonder how it would correctly convert it into a dict, and specifically with the right Dim objects as keys?

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I tested it by setting the Dim object like this

time_data_dim = SpatialDim('time:data')
extern_data_dict = {'data': {
        'dim_tags': [
            batch_dim,
            time_data_dim,
            FeatureDim('feat', 1),
        ],
        'dtype': 'float32',
    }}
dyn_dim_max_sizes={time_data_dim:100}

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I mean, how did you start this script? How did you pass --dyn_dim_min_sizes when starting the script?

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